Migrating from Traditional A/B Testing to Eevy AI

Traditional A/B testing compares two (or sometimes three) variants at a time. With review sections, there are dozens of variables: layout type, card count, sort order, media priority, card style, spacing, arrow type, auto-advance behavior. Testing these one at a time would take years. Testing combinations creates a combinatorial explosion — 5 layout types x 4 card counts x 3 sort orders x 3 card styles = 180 variants. No A/B testing tool can handle this efficiently. Most stores end up testing one or two superficial changes and calling it "optimized."

Genetic algorithms are designed for exactly this kind of multi-variable optimization. Instead of testing pairs, they test entire populations of variants simultaneously. They do not need to test every possible combination — the evolutionary process (selection, crossover, mutation) efficiently navigates the search space, converging on high-performing regions without exhaustively testing every possibility. This means Eevy AI can find optimal configurations in weeks that would take traditional A/B testing months or years to discover. For the full technical explanation, see our genetic optimization guide.

When you switch from manual A/B testing to Eevy AI, expect: First 1-2 weeks: The algorithm explores broadly. RPV may fluctuate as it tests diverse variants, some of which will underperform your previous "winner." This is normal — the algorithm needs to explore before it can optimize. Weeks 2-4: The algorithm begins converging. You will see RPV stabilize and start trending upward. Month 2+: The algorithm has found high-performing configurations and continues to refine them. RPV should be at or above your previous A/B test winner, with continued incremental improvement.

You do not need to discard what your A/B tests taught you. If your tests showed that carousels outperform grids for your store, you can seed the genetic algorithm's initial population with carousel-focused variants. In the section settings, select "Carousel" as the primary layout type — the algorithm will still test variations within that type and occasionally explore others, but your prior learning gives it a head start.

Once Eevy AI is running, you can stop running A/B tests on your review sections through your existing tool. Important: remove any A/B test scripts that modify your review sections to avoid conflicts with Eevy AI's variant serving. If you use your A/B testing tool for other page elements (headlines, CTAs, images), you can keep it for those purposes — it will not conflict with Eevy AI as long as it is not modifying the same DOM elements. For review-specific migration, see also our blog post on A/B testing review widgets.